| Records |
Author  |
Bobrinskiy N.A. |
| Title |
Preditors (Carnivora). The mountains of Central Asia |
Type |
Miscellaneous |
| Year |
1938 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
233-234 |
| Keywords |
Central Asia; mountain system; fauna; snow leopard; wild ibex.; 6340; Russian |
| Abstract |
It describes fauna of the Tien Shan, Pamir and Hissar mountains of Central Asia. The mountains of Central Asia. Ibex (Capra sibirica) and snow leopard (Uncia uncia) are listed among other inhabitants of highlands in Tien Shan and Pamir Hissar. |
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1938 |
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| Language |
Russian |
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| Notes |
Full text available in Russian Journal Title: A course of zoology. |
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no |
| Call Number |
SLN @ rana @ 612 |
Serial |
181 |
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| Author |
Bobrinskiy, N.A. |
| Title |
Subgenus Leopardus |
Type |
Miscellaneous |
| Year |
1935 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
100-101 |
| Keywords |
Ussr; leopards; snow leopard; distribution; features.; 6300; Russian |
| Abstract |
Snow Leopard Felis (Leopardus) uncia S c h r † b., 1778 is distributed in the mountains of Central Asia, Turkmenistan (very rare) and Turkestan, on Tarbagatay, Altay, Sayans and in Uriankhay area. Subspecies haven't been described. Body length is about 130 cm, tail length 90 cm. |
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Full text available in RussianJournal Title: Guide on hunting-game animals of USSR. |
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no |
| Call Number |
SLN @ rana @ 608 |
Serial |
178 |
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| Author |
Bogdanov O.P. |
| Title |
Snow leopard or irbis Uncia Uncia |
Type |
Miscellaneous |
| Year |
1992 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
76-80 |
| Keywords |
Ussr; Uzbekistan; Pamir; tien shan; Hissar ridge; Turkestan ridge; Chatkal ridge; juniper forest; snow leopard; species range; hunting; behavior; diet; reproductive activity; number; ibex; mountain sheep.; 6380; Russian |
| Abstract |
Snow leopard and its habitat within the USSR and Uzbek SSR are described. Its habitat in the Chatkal and Hissar ridges are described too. Given are data concerning alimentary biology, reproduction, and attitude to man. Female snow leopards become mature at the age of two three years, male at the age of four years. Reproduction occurs once every two years. Presumably, there are 10 animals in the country. Snow leopard is protected in four nature reserves in Uzbekistan and a number of nature reserves in neighbour countries. |
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Full text available in RussianJournal Title: Rare and endangered animals of Uzbekistan. Encyclopedic reference book. |
Approved |
no |
| Call Number |
SLN @ rana @ 616 |
Serial |
185 |
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| Author |
Bogdanov O.P. |
| Title |
The Chatkal state mountain forest biosphere reserve. The Hissar nature reserve |
Type |
Miscellaneous |
| Year |
1989 |
Publication |
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Abbreviated Journal |
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Issue |
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Pages |
11-28 |
| Keywords |
Uzbekistan; Chatkal nature reserve; Hissar nature reserve; birds; mammals; amphibians; reptiles; plants; rare species; numerous species; snow leopard.; 6370; Russian |
| Abstract |
In a popular form it describes the origination, nature and fauna of the Chatkal nature reserve. Habitats and ecology of Menzbier's marmot, water-snake, forest dormouse, and fox are described. It also indicates mammal and bird species listed in the Red Book of the USSR black vulture, griffon vulture, bearded vulture, golden eagle, snow leopard, Turkestan lynx, and Tien-Shan brown bear. There are 23 mammal species in the Hissar nature reserve. Ecology of snow leopard and Siberian mountain ibex is described. In the year 1977, 15 Turkestan lynx, about 25 Tien-Shan brown bears, five to seven snow leopards, and 120 150 Siberian mountain ibex were counted in the nature reserve. |
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Full text available in RussianJournal Title: Nature reserves of Uzbekistan. Stories of naturalist. |
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no |
| Call Number |
SLN @ rana @ 615 |
Serial |
184 |
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| Author |
Bogdanov O.P. |
| Title |
Snow leopard (Felis uncia) |
Type |
Miscellaneous |
| Year |
1961 |
Publication |
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Abbreviated Journal |
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Issue |
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Pages |
246-247 |
| Keywords |
Uzbekistan; snow leopard; distriburion; life history; diet; use.; 6360; Russian |
| Abstract |
In Uzbekistan, this species is distributed in spurs of Tien Shan and Gissar. It preys on ibex, rarer on argalis, roe-deers, young wild boars. In winter, it attacks livestock and sometimes feeds upon marmots and smaller rodents. Snow leopard attacks man very rarely, only when wounded. The economic significance of this species is low, since only few skins are traded. Its dressed skins are used as rugs. |
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| Notes |
Full text available in RussianJournal Title: Animals of Uzbekistan. |
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no |
| Call Number |
SLN @ rana @ 614 |
Serial |
183 |
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| Author |
Bohnett, E., Faryabi, S. P., Lewison, R., An, L., Bian, X., Rajabi, A. M., Jahed, N., Rooyesh, H., Mills, E., Ramos, S., Mesnildrey, N., Perez, C. M. S., Taylor, J., Terentyev, V., Ostrowski, S. |
| Title |
Human expertise combined with artificial intelligence improves performance of snow leopard camera trap studies |
Type |
Journal Article |
| Year |
2023 |
Publication |
Global Ecology & Conservation |
Abbreviated Journal |
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| Volume |
41 |
Issue |
e02350 |
Pages |
1-13 |
| Keywords |
Snow leopard, Artificial intelligence, Camera trap misclassification, individual ID, HotSpotter |
| Abstract |
Camera trapping is the most widely used data collection method for estimating snow leopard (Panthera uncia) abundance; however, the accuracy of this method is limited by human observer errors from misclassifying individuals in camera trap images. We evaluated the extent Whiskerbook (www.whiskerbook.org), an artificial intelligence (AI) software, could reduce this error rate and enhance the accuracy of capture-recapture abundance estimates. Using 439 images of 34 captive snow leopard individuals, classification was performed by five observers with prior experience in individual snow leopard ID (“experts”) and five observers with no such experience (“novices”). The “expert” observers classified 35 out of 34 snow leopard individuals, on average erroneously splitting one individual into two, thus resulting in a higher number than true individuals. The success rate of experts was 90 %, with less than a 3 % error in estimating the population size in capture-recapture modeling. However, the “novice” observers successfully matched 71 % of encounters, recognizing 25 out of 34 individuals, underestimating the population by 25 %. It was found that expert observers significantly outperformed novice observers, making statistically fewer errors (Mann Whitney U test P = 0.01) and finding the true number of individuals (P = 0.01). These differences were contrasted with a previous study by Johansson et al. 2020, using the same subset of 16 individuals from European zoos. With the help of AI and the Whiskerbook platform, “experts” were able to match 87 % of encounters and identify 15 out of 16 individuals, with modeled estimates of 16 ± 1 individuals. In contrast, “novices” were 63 % accurate in matching encounters and identified 12 out of 16 individuals, modeling 12 ± 1 individuals that underestimated the population size by 12 %. When comparing the performance of observers using AI and the Whiskerbook platform to observers performing the tasks manually, we found that observers using Whiskerbook made significantly fewer errors in splitting one individual into two (P = 0.04). However, there were also a significantly higher number of combination errors, where two individuals were combined into one (P = 0.01). Specifically, combination errors were found to be made by “novices” (P = 0.04). Although AI benefited both expert and novice observers, expert observers outperformed novices. Our results suggest that AI effectively reduced the misclassification of individual snow leopards in camera trap studies, improving abundance estimates. However, even with AI support, expert observers were needed to obtain the most accurate estimates. |
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| Call Number |
SLN @ rakhee @ |
Serial |
1715 |
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| Author |
Bohnett, E., Holmberg, J., Faryabi, S. P., An, L., Ahmad, B., Rashid, W., Ostrowski, S. |
| Title |
Comparison of two individual identification algorithms for snow leopards (Panthera uncia) after automated detection |
Type |
Journal Article |
| Year |
2023 |
Publication |
Ecological Informatics |
Abbreviated Journal |
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| Volume |
77 |
Issue |
102214 |
Pages |
1-14 |
| Keywords |
Background subtraction, Deep learning, Hotspotter, Individual identification, PIE v2, Snow leopards |
| Abstract |
Photo-identification of individual snow leopards (Panthera uncia) is the primary data source for density estimation via capture-recapture statistical methods. To identify individual snow leopards in camera trap imagery, it is necessary to match individuals from a large number of images from multiple cameras and historical catalogues, which is both time-consuming and costly. The camouflaged snow leopards also make it difficult for machine learning to classify photos, as they blend in so well with the surrounding mountain environment, rendering applicable software solutions unavailable for the species. To potentially make snow leopard individual identification available via an artificial intelligence (AI) software interface, we first trained and evaluated image classification techniques for a convolutional neural network, pose invariant embeddings (PIE) (a triplet loss network), and compared the accuracy of PIE to that of the HotSpotter algorithm (a SIFT-based algorithm). Data were acquired from a curated library of free-ranging snow leopards taken in Afghanistan between 2012 and 2019 and from captive animals in zoos in Finland, Sweden, Germany, and the United States. We discovered several flaws in the initial PIE model, such as a small amount of background matching, that was addressed, albeit likely not fixed, using background subtraction (BGS) and left-right mirroring (LR) techniques which demonstrated reasonable accuracy (Rank 1: 74% Rank-5: 92%) comparable to the Hotspotter results (Rank 1: 74% Rank 2: 84%)The PIE BGS LR model, in conjunction with Hotspotter, yielded the following results: Rank-1: 85%, Rank-5: 95%, Rank-20: 99%. In general, our findings indicate that PIE BGS LR, in conjunction with HotSpotter, can classify snow leopards more accurately than using either algorithm alone. |
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SLN @ rakhee @ |
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1723 |
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| Author |
Bower, J.N. |
| Title |
Shy, elusive, struggling to survive: the snow leopard |
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Journal Article |
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1983 |
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The Explorer |
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9-11 |
| Keywords |
snow leopard |
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SLN @ rana @ 985 |
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187 |
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| Author |
Bower, J.N. |
| Title |
For some endangered species, captive breeding programs are their last chance for life |
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Magazine Article |
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1980 |
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National Parks and Conservation Magazine |
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June |
Pages |
16-19 |
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snow leopard, captive breeding |
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English |
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1209 |
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| Author |
Bowling, B. |
| Title |
The Legal Status of Snow Leopards in Afghanistan |
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Miscellaneous |
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2004 |
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legal; snow leopard; Afghanistan; Cities; Cbd; Convention on Biological Diversity; 5740 |
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United Nations Environment Programme |
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SLN @ rana @ 502 |
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188 |
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